optuna_integration.KerasPruningCallback

class optuna_integration.KerasPruningCallback(trial, monitor, interval=1)

Keras callback to prune unpromising trials.

See the example if you want to add a pruning callback which observes validation accuracy.

Parameters:

• trial (optuna.trial.Trial) – A Trial corresponding to the current evaluation of the objective function.

• monitor (str) – An evaluation metric for pruning, e.g., val_loss and val_accuracy. Please refer to keras.Callback reference for further details.

• interval (int) – Check if trial should be pruned every n-th epoch. By default interval=1 and pruning is performed after every epoch. Increase interval to run several epochs faster before applying pruning.

Methods

on_epoch_end(epoch[, logs])